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ETS: هموارسازی نمایی خطا، روند، فصلی×هموارسازی نمایی ساده و دوگانه (SES / Holt)×
حوزهاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression model
سال پیدایش20081957
پدیدآورHyndman, Koehler, Ord & Snyder (state space framework)Robert G. Brown (SES); Charles C. Holt (linear trend)
نوعExponential smoothing state space modelExponential smoothing forecasting model
منبع بنیادینHyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer. DOI ↗Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗
نام‌های دیگرexponential smoothing state space model, innovations state space model, Holt-Winters family, ETS — Hata/Trend/Mevsimsellik Üstel DüzleştirmeSES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
مرتبط53
خلاصهETS is a comprehensive exponential smoothing framework that automatically selects additive or multiplicative combinations of the error (E), trend (T) and seasonal (S) components of a time series. Formalised as an innovations state space model by Hyndman, Koehler, Ord and Snyder in 2008, it unifies and generalises the Holt-Winters family of forecasting methods.Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta.
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ScholarGateمقایسهٔ روش‌ها: ETS Model · Exponential Smoothing. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare